Improved Indirect Power Control (IDPC) of Wind Energy Conversion Systems (WECS) [1 ed.] 9789811412677, 9789811412660

Citation preview

Improved Indirect Power Control (IDPC) of Wind Energy Conversion Systems (WECS) Authored by Fayssal Amrane

LAS Research Laboratory Department of Electrical Engineering, University of Setif-1, Setif, Algeria

& Azeddine Chaiba Department of Industrial Engineering, University of Khenchela, Algeria

Improved Indirect Power Control (IDPC) of Wind Energy Conversion Systems (WECS) Authors: Fayssal Amrane and Azeddine Chaiba ISBN (Online): 978-981-14-1267-7 ISBN (Print): 978-981-14-1266-0 © 2019, Bentham eBooks imprint. Published by Bentham Science Publishers Pte. Ltd. Singapore. All Rights Reserved. First published in 2019.

BENTHAM SCIENCE PUBLISHERS LTD.

End User License Agreement (for non-institutional, personal use) This is an agreement between you and Bentham Science Publishers Ltd. Please read this License Agreement carefully before using the ebook/echapter/ejournal (“Work”). Your use of the Work constitutes your agreement to the terms and conditions set forth in this License Agreement. If you do not agree to these terms and conditions then you should not use the Work. Bentham Science Publishers agrees to grant you a non-exclusive, non-transferable limited license to use the Work subject to and in accordance with the following terms and conditions. This License Agreement is for non-library, personal use only. For a library / institutional / multi user license in respect of the Work, please contact: [email protected].

Usage Rules: 1. All rights reserved: The Work is the subject of copyright and Bentham Science Publishers either owns the Work (and the copyright in it) or is licensed to distribute the Work. You shall not copy, reproduce, modify, remove, delete, augment, add to, publish, transmit, sell, resell, create derivative works from, or in any way exploit the Work or make the Work available for others to do any of the same, in any form or by any means, in whole or in part, in each case without the prior written permission of Bentham Science Publishers, unless stated otherwise in this License Agreement. 2. You may download a copy of the Work on one occasion to one personal computer (including tablet, laptop, desktop, or other such devices). You may make one back-up copy of the Work to avoid losing it. 3. The unauthorised use or distribution of copyrighted or other proprietary content is illegal and could subject you to liability for substantial money damages. You will be liable for any damage resulting from your misuse of the Work or any violation of this License Agreement, including any infringement by you of copyrights or proprietary rights.

Disclaimer: Bentham Science Publishers does not guarantee that the information in the Work is error-free, or warrant that it will meet your requirements or that access to the Work will be uninterrupted or error-free. The Work is provided "as is" without warranty of any kind, either express or implied or statutory, including, without limitation, implied warranties of merchantability and fitness for a particular purpose. The entire risk as to the results and performance of the Work is assumed by you. No responsibility is assumed by Bentham Science Publishers, its staff, editors and/or authors for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products instruction, advertisements or ideas contained in the Work.

Limitation of Liability: In no event will Bentham Science Publishers, its staff, editors and/or authors, be liable for any damages, including, without limitation, special, incidental and/or consequential damages and/or damages for lost data and/or profits arising out of (whether directly or indirectly) the use or inability to use the Work. The entire liability of Bentham Science Publishers shall be limited to the amount actually paid by you for the Work.

General: 1. Any dispute or claim arising out of or in connection with this License Agreement or the Work (including non-contractual disputes or claims) will be governed by and construed in accordance with the laws of Singapore. Each party agrees that the courts of the state of Singapore shall have exclusive jurisdiction to settle any dispute or claim arising out of or in connection with this License Agreement or the Work (including non-contractual disputes or claims). 2. Your rights under this License Agreement will automatically terminate without notice and without the

need for a court order if at any point you breach any terms of this License Agreement. In no event will any delay or failure by Bentham Science Publishers in enforcing your compliance with this License Agreement constitute a waiver of any of its rights. 3. You acknowledge that you have read this License Agreement, and agree to be bound by its terms and conditions. To the extent that any other terms and conditions presented on any website of Bentham Science Publishers conflict with, or are inconsistent with, the terms and conditions set out in this License Agreement, you acknowledge that the terms and conditions set out in this License Agreement shall prevail. Bentham Science Publishers Pte. Ltd. 80 Robinson Road #02-00 Singapore 068898 Singapore Email: [email protected]

CONTENTS FOREWORD ........................................................................................................................................... i PREFACE ................................................................................................................................................ HOW TO USE THIS BOOK ......................................................................................................... CONSENT FOR PUBLICATION ................................................................................................ CONFLICT OF INTEREST ......................................................................................................... ACKNOWLEDGEMENTS ...........................................................................................................

ii ii ii ii ii

CHAPTER 1 GENERAL INTRODUCTION ..................................................................................... 1. INTRODUCTION ...................................................................................................................... 2. THE MAIN CONTRIBUTIONS ........................................................................................ 3. WORK LIMITATIONS ...................................................................................................... REFERENCES ...............................................................................................................................

1 1 3 6 6

CHAPTER 2 OVERVIEW OF WIND ENERGY CONVERSION SYSTEMS (WECS) ............... 1. WIND POWER DEVELOPMENT ........................................................................................... 2. WIND TURBINE CONCEPTS ................................................................................................. 2.1. Fixed Speed Wind Turbines (WT Type A) ...................................................................... 2.2. Partial Variable Speed Wind Turbine (VS-WT) Using Variable Rotor Resistance (Type B) ............................................................................................................................................. 2.3. VS-WT Using Partial Scale Power Converter (WT Type C) .......................................... A-Advantages of the DFIG [7] ............................................................................................... B-Drawbacks of the DFIG [8 - 11] ......................................................................................... 2.4. VS-WT using Full Scale Power Converter (Type D) ...................................................... 3. CONTROL STRUCTURE OF WTS ........................................................................................ 4. LITERATURE SURVEY .......................................................................................................... 4.1. Modelling of a WTGS ..................................................................................................... A- Modelling of DFIG ............................................................................................................ 4.2. Control Strategies for a WT-GS ...................................................................................... A-Maximum Power Point Tracking (MPPT) Control ............................................................ A.1 Intelligent Control ............................................................................................................ A.2 Other Control Strategies ................................................................................................... B-DFIG Control ...................................................................................................................... B.1 Field Oriented Control ..................................................................................................... B.2 Direct Torque/Power Control (DTC/DPC) ...................................................................... B.3 Adaptive Nonlinear Control (MRAS Observer/MRAC Controller) ................................ B.4 Adaptive Disturbance Rejection Control (ADRC) ........................................................... B.5 Sliding Mode Control (SMC) ........................................................................................... B.6 Backstepping Control (BSC) ............................................................................................ B.7 Predictive Direct Power Control (PDPC) and Deadbeat Control .................................... B.8 Input/Output Linearizing and Decoupling Control .......................................................... NOTES ............................................................................................................................................. REFERENCES ...............................................................................................................................

9 9 11 11

CHAPTER 3 INDIRECT POWER CONTROL (IDPC) OF DFIG USING CLASSICAL & ADAPTIVE CONTROLLERS UNDER MPPT STRATEGY ............................................................ 1. INTRODUCTION ...................................................................................................................... 2. MATHEMATICAL MODEL OF DFIG .................................................................................. 3. CONVENTIONAL INDIRECT POWER CONTROL (IDPC) OF DFIG ............................ 3.1. Relationship Between Rotor Voltages and Rotor Currents (Generally Form) ................ 3.2. Relationship Between Stator Power and Rotor Currents .................................................

12 12 12 12 12 13 14 15 15 15 15 16 16 16 16 16 17 17 18 18 19 19 21 21 26 26 28 30 32 33

3.3. Relationship Between Rotor Voltages and Rotor Currents (Detailed Form) .................. 3.4. Synthesis of the Proportional-Integral (PI) Regulator ..................................................... 4. WIND TURBINE MATHEMATICAL MODEL .................................................................... 4.1. Maximum Power Point Tracking (MPPT) Strategy ........................................................ 5. GRID SIDE CONVERTER (GSC) AND DC-LINK VOLTAGE CONTROL [27 - 29] ...... 6. ROTOR SIDE CONVERTER (RSC) ....................................................................................... 6.1. Space Vector Modulation (SVM) [31, 32] ...................................................................... 6.2. LC Filter ........................................................................................................................... 7. OPERATING PRINCIPLE OF DFIG ...................................................................................... 8. EXPERIMENTAL RESULTS OF CLASSICAL POWER CONTROL UNDER SUBSYNCHRONOUS & SUPER-SYNCHRONOUS OPERATIONS ............................................ 9. PROPOSED IDPC BASED ON PID CONTROLLERS ......................................................... 9.1. Advantages ....................................................................................................................... 9.2. Drawbacks ........................................................................................................................ 10. PROPOSED IDPC BASED ON MRAC CONTROLLERS ................................................. 10.1. Definition ....................................................................................................................... 10.2. Description ..................................................................................................................... 10.3. Some Mechanisms Causing Variation in Process Dynamics Are ................................. 10.4. Advantages ..................................................................................................................... 10.5. Drawbacks ...................................................................................................................... 11. SIMULATION RESULTS ....................................................................................................... 11.1. Mode 1 (Based on PI, PID and MRAC Without MPPT Strategy) ................................ 11.2. Mode 2 (Based on PI, PID and MRAC with MPPT Strategy- Step Wind Speed) ........ 11.3. Mode 3 (Based on PI, PID and MRAC with MPPT Strategy- Random Wind Speed) 11.4. Robustness Tests12 for Mode 1, Mode 2 & Mode 3 ..................................................... CONCLUSION ............................................................................................................................... NOTES ............................................................................................................................................. REFERENCES ............................................................................................................................... CHAPTER 4 A NOVEL IDPC USING SUITABLE CONTROLLERS (ROBUST AND INTELLIGENT CONTROLLERS) ...................................................................................................... 1. INTRODUCTION ...................................................................................................................... 2. DRAWBACKS AND PERFORMANCES LIMITATION OF CONVENTIONAL IDPC ........................................................................................................................................................... 3. PROPOSED POWER CONTROL BASED ON TYPE-1 FUZZY LOGIC CONTROL (T1-FLC) .......................................................................................................................................... 3.1. Reasons for Choosing Fuzzy Logic ................................................................................. 3.2. Fuzzy Set Theory and Fuzzy Set Operations ................................................................... 3.3. Membership Functions ..................................................................................................... 3.4. Mamdani Fuzzy Inference Method .................................................................................. A- Fuzzifier ............................................................................................................................. B- Knowledge Base ................................................................................................................ C- Inference Engine ................................................................................................................ D- Defuzzifier ......................................................................................................................... 3.5. MEMBERSHIP FUNCTIONS AND RULE BASE .............................................................. 4. PROPOSED POWER CONTROL BASED ON TYPE-2 FUZZY LOGIC CONTROL (T2-FLC) .......................................................................................................................................... 4.1. Overview of Type-2 Fuzzy Logic Controller Toolbox .................................................... 4.2. Design of Type-2 Fuzzy Logic Controller ....................................................................... 5. PROPOSED POWER CONTROL BASED ON NEURO-FUZZY CONTROL (NFC) ...... 5.1. Layer I: Input layer .......................................................................................................... 5.2. Layer II: membership layer ..............................................................................................

34 35 37 39 42 44 46 52 56 59 59 61 61 62 62 62 62 62 62 65 68 74 77 79 81 82 82 86 86 88 89 89 90 91 91 91 92 92 92 93 96 97 98 101 102 103

5.3. Layer III: rule layer .......................................................................................................... 5.4. Layer IV: output layer ...................................................................................................... 6. SIMULATION RESULTS ......................................................................................................... 6.1. Mode 1 (Based on T1-FLC, T2-FLC 3x0026; NFC, Without MPPT Strategy) ............. A-Novel IDPC based on T1-FLC: (Fig. 4.16 to the left side): ...................................... B-Novel IDPC based on T2-FLC: (Fig. 4.16 to the middle side): ................................ C-Novel IDPC based on NFC: (Fig. 4.16 to the right side): ........................................ 6.2. Mode 2 (Based on T1-FLC, T2-FLC NFC, with MPPT Strategy- Step Wind Speed) .... A- Novel IDPC based on T1-FLC: (Fig. 4.17 to the left side): ..................................... B- Novel IDPC based on T2-FLC: (Fig. 4.17 to the middle side): ............................... C- Novel IDPC based on NFC: (Fig. 4.17 to the right side): ....................................... B-Novel IDPC based on T2-FLC: (Fig. 4.18 to the middle side): ................................ C-Novel IDPC based on NFC: (Fig. 4.18 to the right side): ........................................ 6.3. Mode 3 (Based on T1-FLC, T2-FLC NFC, with MPPT Strategy- Random wind Speed) A-Novel IDPC based on T1-FLC: (Fig. 4.19 to the Left Side): .................................... B-Novel IDPC based on T2-FLC: (Fig. 4.19 to the Middle Side): ............................... C-Novel IDPC based on NFC: (Fig. 4.19 to the Right Side): ....................................... 6.4. Robustness Tests7 for Mode 1, Mode 2 Mode 3 ............................................................. A-Mode 1 (Novel IDPC based on T1-FLC, T2-FLC NFC): ......................................... B-Mode 2 (Novel IDPC based on T1-FLC, T2-FLC NFC): ......................................... C-Mode 3 (Novel IDPC based on T1-FLC, T2-FLC NFC): ......................................... 7. WIND-SYSTEM PERFORMANCES RECAPITULATION UNDER SIX (06) PROPOSED IDPC ALGORITHMS ............................................................................................. CONCLUSION ............................................................................................................................... NOTES ............................................................................................................................................. REFERENCES ...............................................................................................................................

103 103 105 108 108 108 108 109 109 109 109 112 112 112 112 112 114 114 115 115 115 117 118 118 119

CHAPTER 5 GENERAL CONCLUSION .......................................................................................... 121 5.1. FUTURE WORKS ........................................................................................................... 122 APPENDIX A: WECS PARAMETERS ............................................................................................... 123 LIST OF ABBREVIATIONS ................................................................................................................. 126 LIST OF ACRONYMS ........................................................................................................................... 128 SUBJECT INDEX ................................................................................................................................... 131

i

FOREWORD During the past decade, the installed wind power capacity in the world has been increasing more than 30%. Wind energy conversion system (WECSs) based on the doubly-fed induction generator (DFIG) dominated the wind power generations due to the outstanding advantages, including small converters rating around 30% of the generator rating, lower converter cost. Due to the non-linearity of wind system, the DFIG power control presents a big challenge especially under wind-speed variation and parameter’s sensibility. To overcome these major problems; an improved IDPC (Indirect Power Control); based on PID “Proportional-Integral-Derivative” controller, was proposed instead the conventional one (based on PI), in order to enhance the wind-system performances in terms; power error, tracking power and overshoot. Unfortunately using robustness tests (based on severe DFIG’s parameters changement); the wind-system offers non-satisfactory simulation results which were illustrated by the very bad power tracking and very big overshoot (> 50%). In this context; adaptive, robust & intelligent controllers were proposed to control direct & quadrature currents (Ird & Irq) under MPPT (Maximum Power Point Tracking) strategy to main the unity power factor (PF≈1) by keeping the reactive power at zero level. In this case, the new IDPC based on intelligent controllers offered an excellent wind-system performance especially using robustness tests, which offered a big improvement especially using Type-1 Fuzzy Logic Controller (T1-FLC), Type-2 Fuzzy Logic Control (T2-FLC; is the New class of fuzzy logic) & Neuro-Fuzzy Logic (NFC). In this sense, I think that this edited book is an important contribution to help students already in mastery of the basis of power electronic circuits and control systems theory to achieve these pedagogical goals. The proposed book describes with easy manner the modeling & control of Wind-turbine DFIG in order to control the stator powers using different topologies of robust, adaptive and intelligent controllers. The book present numerous intelligent control techniques that help in the control design of the DFIG wind-system (WT). The textbook “Improved Indirect Power Control (IDPC) of Wind Energy Conversion Systems (WECS)” proposes a collection of concepts, organized in a synergic manner such that to ease comprehension of the WT control design. The book’s contribution goes towards completing the already existing literature by offering a useful integration of control techniques, worthy to be read, understood and employed in the various WT applications. Please enjoy reading this book.

Dr. Ali CHEBABHI ICEPS (Intelligent Control & Electrical Power Systems), Sidi-Bel-Abbes Mohamed El Bachir El Ibrahimi University, BBA, Algeria

ii

PREFACE HOW TO USE THIS BOOK This book offers advanced Power Control such as: Indirect Power Control (IDPC) to overcome wind-system DFIG limitation performances under different wind speed and parameters changement conditions. This book is addressed to students of: License, Master degrees and also for Post-graduation (PhD students) in order to understand the wind-system basics especially: Power electronics control (in this proposed Book we used SVM in order to fix the switching frequency), Powerflow DFIM diagram & Maximum power point tracking strategy.

CONSENT FOR PUBLICATION Not applicable.

CONFLICT OF INTEREST The authors declare no conflict of interest, financial or otherwise.

ACKNOWLEDGEMENTS Firstly, I would like to thank Allah, for His mercy on me during all my life, and praise Prophet MOHAMMAD (Peace be upon him!). I would like to express my appreciation to all those who gave me the possibility to complete this book. I wish to express my best gratitude and thanks to my Co-Editor, Pr Azeddine CHAIBA, for his technical guidance, his intellectual support and encouragement of my research work.

Fayssal Amrane LAS Research Laboratory Department of Electrical Engineering University of Setif-1, Setif Algeria Azeddine Chaiba Department of Industrial Engineering University of Khenchela Algeria

Improved Indirect Power Control of Wind Energy Conversion Systems, 2019, 1-8

1

CHAPTER 1

General Introduction Abstract: In this chapter, a brief general introduction focuses on the well-known topologies of wind energy conversion systems (WECS), on proposed controls and generators by the scientific researchers. One part will be devoted to the latest research that has addressed the performance problems of wind systems and their results (in simulation). There will be also some arguments that reflect the main proposed ideas in this eBook, the proposed selections and their applications in simulation. We present the selecting criteria in particular the type of: generator, controls and theirs application in simulation studies. Also, we discuss in a detailed section on the different contributions of eBook that define the improvement of the proposed algorithms in each chapter. Furthermore, the organization and structure of eBook will be as follow; chapter one is devoted on the state of the art of wind systems and their controls, in particular using the doubly fed induction machine (DFIM). The simulation part is provided in two chapters (3 and 4). The limitations and problems encountered during the realization of this eBook are well described in the following section. After solving problems, very satisfactory simulation results have been found which reflect the quality of the scientific contribution including more papers of conferences; Journal papers were published during this eBook.

Keywords: Doubly Fed Induction Generator (DFIG), Power Electronics (PEs), Wind Energy Conversion Systems (WECS’s), Wind Turbines (WTs). 1. INTRODUCTION The growing connection of wind turbines has augmented at a quick pace over the last years. Installed wind power production, which is presently higher than 440 GW, is predictable to surpass 760 GW by 2020, creation this form of renewable energy an important element of the current and future energy supply systems [1 3]. The wind energy raises more important than any other renewable energy sources and is becoming really a significant factor in the recent energy supply system [4]. In the 1980, the PEs (Power Electronics) WTs (wind turbines) was a soft starter used to primarily interconnect the induction generator with the electrical grid, only thysistors were used and they did not require to carry the power continuously [5]. Fayssal Amrane & Azeddine Chaiba All rights reserved-© 2019 Bentham Science Publishers

2 Improved Indirect Power Control of Wind Energy Conversion Systems

Amrane and Azeddine

In the 1990s the PE technology was essentially used for the rotor resistance control of wound-rotor induction generator (WRIG), where further advanced diode bridges with a chopper were used to control the rotor resistance for generator [6], particularly at rated power process to reduce loading and mechanical stress. Since 2000, the bidirectional power flow have introduced with more progressive voltage source converters; the PEs started to handle the produced power from the WTs, first, by partial scale of power capacity for doubly fed induction generators (DFIGs), and then by the full scale of power capacity for asynchronous or synchronous generators (A/SGs) [5, 6]. Although the WTs can be considered into various structures in terms of the generator type, with/without the gearbox, or the rating of the power electronic converter, it is common to divide the WTs system into a partial-scale power converter equipped with a DFIG and a full-scale power converter together with either a synchronous generator (SG) or an induction generator (IG) [7, 8]. Presently, the DFIG system configuration the occupies close to 50% of the wind energy market, due to its small size, light weight, and cost-effectiveness of the generator, as well as the relatively small and economic power converter [9, 10]. The variable-speed WECSs can be worked in the maximum power point tracking (MPPT) mode to extract the maximum energy from wind. For this raison, goodcalibrated mechanical sensors, such as encoders and anemometers/ resolvers, are essential in order to obtain the information of wind speed and generator rotor speed/position. But, the usage of mechanical sensors raises the cost, hardware difficulty of WECSs [11, 12]. These difficulties can be resolved by adopting position/speed sensorless control schemes [13]. The DFIG’ conventional control approaches are generally based on Field oriented control (FOC) algorithms [14, 15]. In the past few years it suffers from the handicap of the generator parameters changement, which comes to compromise the robustness of the control device. Hence, the regulator should accommodate the effects of uncertainties and maintain the system steady against a big variation of system parameters. The traditional PI-based controllers cannot totally fulfill stability and performance necessities [15]. Their optimal PI’s parameters can be defined by other approaches such as genetic algorithm (GA) or particle swarm optimization (PSO) [16 - 18]. Power converter and drive system have inherent features, such as non-linearities, inaccessibility of an accurate model or excessive complexity, that call for intelligent control approaches such as neural networks (NN), fuzzy logic (FL) [19, 20]. The dynamic performance of a WTS can be substantially enhanced by the application of smart methods for the PES control that are used in WPG systems. Hence, the aims of efficient wind power integration in the power system can be successfully accomplied.

General Introduction

Improved Indirect Power Control of Wind Energy Conversion Systems 3

Fuzzy logic (FL) has been applied for WPG control [21, 22]. The FL based controller is able to be implant, in the control strategy, the qualitative knowledge of an operator or field engineer about the system, but has been assessed for its limits, such as the lack of a formal design methodology, the difficulty in predicting stability and robustness of FL controlled systems [23]. The artificial neural networks (ANNs) based controllers have been used as these controllers can be formed straight by using the input-output information of the indefinite system, without requirement any previous model structure. However, to choice an ideal structure, parameter values and the number of training sets are still crucial concerns. To take benefit of their strengths and to mitigate their disadvantages, numerous hybrid methods have been planned [24]. A hybrid system can be achieved by, for example, combining a fuzzy inference system and adaptive neural networks (i.e., the adaptive neuro-fuzzy inference system (ANFIS)) [25]. ANFIS based controllers have been successfully implemented for numerous power systems and PE applications [26, 27]. On the other side, the system is greatly nonlinear. Thus, linearization operating point cannot be applied to design the controller. Nonlinear control methods can be used to efficiently solve this problem [28, 29]. In attempt to reach high performances in the steady and stransient states, a diverse nonlinear control configuration must be applied. In the recent years, several modified nonlinear state feedback such as Input-output feedback linearization control (I/OLC), Sliding Mode Control (SMC); Backstepping Mode Control (BMC) and Model Predictive control (MPC) have been applied to more develop the control performances [30]. 2. THE MAIN CONTRIBUTIONS In the review of the DFIG-based wind system in last decade, it can be seen that the majority relies on the regulation of: speed, flux, torque, current and powers. More than 75% of the published articles (mainly based on “IEEE and Science Direct” databases between 2005 and 2017) concerning the study and development of the DFIG-based wind system are basically focused on three (03) main controls: vector control (rotor flux and torque), predictive control and direct power control (stator active and reactive power). In this eBook, we are interested in power control (in terms of modeling) whose main objective is to improve the quality of energy transmitted into the network by integrating and developing new algorithms in order to overcome or mitigate drawbacks of conventional controls in transient and steady states during the wind speed variation and under robustness tests. A detailed simulation study in power control using PI (Proportional-Integral) regulators (in order to control the stator powers “Ps and Qs” and the rotor currents

4 Improved Indirect Power Control of Wind Energy Conversion Systems

Amrane and Azeddine

“Ird and Irq” according to 04 loops respectively) is developed according to three modes, as follows: ● ● ●

Mode 1: Without the MPPT strategy (imposed power profiles). Mode 2: With the MPPT strategy (wind in step form). Mode 3: With the MPPT strategy (wind in random form).

(Knowing that all control algorithms in this eBook are developed using these three modes). The MPPT (maximum power point tracking) is used in order to extract the maximum power despite the wind speed variation (step or random wind forms) by maintaining the reactive power at zero level means power factor near to the unity. Some drawbacks appears in simulation studies especially in with/without robustness tests (Knowing that we used the same robustness tests in chapters: 3 and 4) such as: ● ●

●

●

●

●

●

An important overshoot is noted (more than + 50%). The coupling terms between the parameters of the both axes (d and q) has negative influence on the wind-system performances, especially in high windpower generation (HWPG). The long response time (a visible delay of the measured value relative to that of the reference) order of 10e-2 (sec). A bad power tracking of the measured value relative to that of the reference especially if the profile is in the step form. Poor power/voltage quality which will be transmitted to the grid; a bad THD that exceeds IEEE standards (>> + 5%). A remarkable power error for conventional power control sometimes exceeding 25% of the rated power (± 1000 (W) for a rated power of 4 kW). The conventional regulators (PI regulators) depend on the DFIG's parameters.

In this context, several approaches have been proposed in order to overcome or minimize these drawbacks (already mentioned above). As a first step, a conventional regulator called PID (Proportional-Integral-Derivate) more developed in term of minimization error and overshoot is proposed instead the PI controllers to control Ps, Qs, Irq and Ird respectively. Remarkable improved performances are noted for the three modes -Mode: 1, Mode: 2 and Mode: 3; already mentioned above- especially without robustness tests. After applying the 3rd test (green color of the curves/robustness tests section in each chapter) a bad tracking of the active power is particularly apparent when the wind speed varies severely, which means that the PID regulator -for rotor current control: Ird and

General Introduction

Improved Indirect Power Control of Wind Energy Conversion Systems 5

Irq- is unable to track the power reference during the sudden wind speed variation and DFIG’s parameters variation. For this reason, intelligent controllers are used to correct the failure of conventional controllers in transient and steady states, such as: “Type-1 Fuzzy Logic Control (T1-FLC)”, “T2-FLC (Type-2 fuzzy logic control)” and “NFC (Neuro-fuzzy control)”; knowing that all these proposed controllers (already mentioned above) are used in order to control the d-q axes rotor currents components (Ird and Irq) by keeping PID controllers for stator active and reactive powers tuning (Ps and Qs). Intelligent regulators have been proposed for the control of “Irq and Ird“, in same time; there will be more improved results than used only for “Ps, Qs, Irq and Ird“, the aim of this select is minimizing time computing and in same time maintaining a good performance, then it is to look for a robust controllers which does not depend on DFIG’s mathematical model. In this context, the high-performance regulators known by the name of “intelligent regulators”; are set up to remedy these problems -performances limitation-, three (03) intelligent regulators: T1-FLC, T2-FLC and NFC are used to correct power error especially under robustness tests. T2-FLC and T1-FLC are fuzzy controllers based on the inferences (inputs and outputs in triangular or trapezoid forms) and linguistic rules -depends on the inferences number choosing for studied system to the power of number of inputs, exp: 7 inferences in triangular form “for inputs and output respectively” and 2 inputs; means: 72 =49 rules - to initiate the optimal calculation of the desired value, noting that the computational algorithm interface is integrated in MATLAB®/Simulink software. Knowing that; T2-FLC controller based on three (03) dimensions more than T1FLC (only two dimensions), this difference in dimensional form generates a complexity of mathematical model of the controller itself and aims to minimize error of the desired value known by optimal value despite the parameters variation of the wind-system. T2-FLC represents the most developed fuzzy family generation in terms of precision and robustness. NFC regulator is a combination between the fuzzy logic strategy and the artificial neural network (ANN) to have theirs qualities at the same time: to remedy the dependence problem of the wind-system mathematical model and to minimize the calculation of the optimal value while maintaining the robustness despite the parametric variation. Excellent results have been found compared to those found for the last proposed controllers which reflect the robustness of the proposed controller.

6 Improved Indirect Power Control of Wind Energy Conversion Systems

Amrane and Azeddine

3. WORK LIMITATIONS We found several problems and the majority of them were reminted i.e.; the Simpower Systems model in Matlab/Simulink takes a long time in simulation; sometimes for several minutes especially if the sampling time is between 1e-6 (sec) and 1e-5 (sec), and this can cause problems in the computer (the PC). If the studied system includes a simple algorithm with a few Simulink-blocks (maximum 2 control loops) this does not pose a problem in general, and if the studied system is complicated with several loops -as in the majority of the algorithms of this eBook- the solution is translated in this case by the realization of the blocks based on the mathematical model of the studied system because the Simpower Systems library contains dozens of algorithms in the same block means that; the studied system is near to the real one; exp: DTC control. By using these simulation blocks, the simulation time is minimized to just a few seconds. It is necessary to note that the calculation time of the proposed power algorithm using T2-FLC will be took more time (nearly twice) than T1-FLC; the reason was the complexity of T2-FLC structure (using three (03) dimensions) compared to T1FLC (based only on two (02) dimensions). REFERENCES [1]

F. Blaabjerg, and K. Ma, "Wind Energy Systems", Proc. IEEE, vol. 105, no. 11, pp. 2116-2131, 2017. [http://dx.doi.org/10.1109/JPROC.2017.2695485]

[2]

Ren21, "Renewables 2016: Global Status Report (GSR)", http://www.ren21.net

[3]

Gwec, "Global Wind Statistics 2016", www.gwec.net

[4]

F. Blaabjerg, and K. Ma, "Future on Power Electronics for Wind Turbine Systems", IEEE J. Emer. Selec. Topcs. Power. Electron., vol. 1, no. 3, 2013. [http://dx.doi.org/10.1109/JESTPE.2013.2275978]

[5]

Z. Chen, J.M. Guerrero, and F. Blaabjerg, "A review of the state of the art of power electronics for wind turbines", IEEE Trans. Power Electron., vol. 24, no. 8, pp. 1859-1875, 2009. [http://dx.doi.org/10.1109/TPEL.2009.2017082]

[6]

A.D. Hansen, F. Iov, F. Blaabjerg, and L.H. Hansen, "Review of contemporary wind turbine concepts and their market penetration", J. Wind Eng., vol. 28, no. 3, pp. 247-263, 2004. [http://dx.doi.org/10.1260/0309524041590099]

[7]

V. Yaramasu, B. Wu, P.C. Sen, S. Kouro, and M. Narimani, "High-power wind energy conversion systems: State-of-the-art and emerging technologies", Proc. IEEE, vol. 103, no. 5, pp. 740-788, 2015. [http://dx.doi.org/10.1109/JPROC.2014.2378692]

[8]

D. Zhou, and F. Blaabjerg, "Bandwidth oriented proportional-integral controller design for back-to -back power converters in DFIG wind turbine system", IET Renew. Power Gener., vol. 11, no. 7, pp. 941-951, 2017. [http://dx.doi.org/10.1049/iet-rpg.2016.0760]

[9]

M. Liserre, R. Cardenas, M. Molinas, and J. Rodriguez, "Overview of multi-MW wind turbines and wind parks", IEEE Trans. Ind. Electron., vol. 58, no. , 4, pp. 1081-1095, 2011. [http://dx.doi.org/10.1109/TIE.2010.2103910]

[10]

R. Cardenas, R. Pena, S. Alepuz, and G. Asher, "Overview of control systems for the operation of

General Introduction

Improved Indirect Power Control of Wind Energy Conversion Systems 7

DFIGs in wind energy applications", IEEE Trans. Ind. Electron., vol. 60, no. 7, pp. 2776-2798, 2013. [http://dx.doi.org/10.1109/TIE.2013.2243372] [11]

Y. Zhao, C. Wei, Z. Zhang, and W. Qiao, "A Review on Position/Speed Sensorless Control for Permanent-Magnet Synchronous Machine-Based Wind Energy Conversion Systems", IEEE J. Emerg. Sel. Top. Power Electron., vol. 1, no. 4, pp. 203-216, 2013. [http://dx.doi.org/10.1109/JESTPE.2013.2280572]

[12]

W. Qiao, X. Yang, and X. Gong, "Wind speed and rotor position sensorless control for direct-drive PMG wind turbines", IEEE Trans. Ind. Appl., vol. 48, no. 1, pp. 3-11, 2012. [http://dx.doi.org/10.1109/TIA.2011.2175877]

[13]

W. Qiao, "Intelligent mechanical sensorless MPPT control for wind energy systems", Proc. IEEE Power and Energy Society General Meeting, 2012 pp. 1-8

[14]

N. Khemiri, A. Khedher, and M.F. Mimoun, "Wind Energy Conversion System using DFIG Controlled by Backstepping and Sliding Mode Strategies", Int. J. Renew. Energy Res., vol. 2, no. 3, pp. 3-11, 2012.

[15]

Á. Luna, K. Lima, P. Rodríguez, E.H. Watanabe, and R. Teodorescu, "Comparison of Power Control Strategies for DFIG Wind Turbines", Industrial Electronics, IECON 2008. 34th Annual Conference of IEEE, 2008 [http://dx.doi.org/10.1109/IECON.2008.4758286]

[16]

B. Yang, L. Jiang, L. Wang, W. Yao, and Q.H. Wu, "Nonlinear maximum power point tracking control and modal analysis of DFIG based wind turbine", Industrial Electronics, Electrical Power and Energy Systems., vol. 74, no. xx, pp. 429-436, 2016. [http://dx.doi.org/10.1016/j.ijepes.2015.07.036]

[17]

M. Rahimi, and M. Parniani, "Dynamic behavior analysis of doubly-fed induction generator wind turbines-the influence of rotor and speed controller parameters", Int. J. Electr. Power Energy Syst., vol. 32, pp. 464-477, 2010. [http://dx.doi.org/10.1016/j.ijepes.2009.09.017]

[18]

F. Wu, X-p. Zhang, K. Godfrey, and P. Ju, "Small signal stability analysis and optimal control of a wind turbine with doubly fed induction generator", IET Gener. Transm. Distrib., vol. 1, no. 5, pp. 751760, 2007. [http://dx.doi.org/10.1049/iet-gtd:20060395]

[19]

G.C.D. Sousa, and B.K. Bose, "Fuzzy logic applications to power electronics and drives – an overview", Proc. IECON 1995, 1995pp. 57-62 [http://dx.doi.org/10.1109/IECON.1995.483333]

[20]

Y. Dote, and R.G. Hoft, Intelligent Control: Power Electronic Systems Oxford University Press: NewYork, 1998.

[21]

M.G. Simoes, B.K. Bose, and R.J. Spiegel, "Design and performance evaluation of a fuzzy-logi-based variable-speed wind generation system", IEEE Trans. Ind. Appl., vol. 33, no. 4, pp. 956-965, 1997. [http://dx.doi.org/10.1109/28.605737]

[22]

H.M. Soloumah, and N.C. Kar, "Fuzzy logic based vector control of a doubly-fed induction generator for wind power application", Wind Eng., vol. 30, no. 3, pp. 201-224, 2006. [http://dx.doi.org/10.1260/030952406778606232]

[23]

B. Singh, E. Kyriakides, and S.N. Singh, "Intelligent Control of Grid Connected Unified Doubly-Fed Induction Generator", IEEE Conference, 2010 [http://dx.doi.org/10.1109/PES.2010.5589896]

[24]

P. vas, Artificial-intelligence-based electrical machines and drives Oxford University Press: NewYork, 1999.

[25]

J.h. Roger Jang, "ANFIS: Adaptive-network based fuzzy inference system", IEEE Trans. Syst. Man

8 Improved Indirect Power Control of Wind Energy Conversion Systems

Amrane and Azeddine

Cybern., vol. 23, no. 2, pp. 665-685, 1993. [http://dx.doi.org/10.1109/21.256541] [26]

P. Tripathy, "Development of Adaptive Supplementary Feedback Controller for GUPFC", Master Thesis (in English Language), IIT Kanpur, India, 2006.

[27]

C. Potter, and M. Negnevitsky, "Very short-term wind forecasting for Tasmanian power generation", IEEE Trans. Power Syst., vol. 21, no. 2, pp. 965-972, 2006. [http://dx.doi.org/10.1109/TPWRS.2006.873421]

[28]

J. Karthikeyan, S.K. Kummara, C. Nagamani, and G.S. Ilango, "Power control of grid connected Doubly Fed Induction Generator using Adaptive Back Stepping approach“, in Proc", 10th IEEE International Conference on Environment and Electrical Engineering EEEIC’2011, 2011 Rome [http://dx.doi.org/10.1109/EEEIC.2011.5874758]

[29]

K. Abbaszadeh, and S. Roozbehani, "A New Approach for Maximum Power Extraction from Wind Turbine Driven by Doubly Fed Induction Generator Based on Sliding Mode Control", Energ. Manag., vol. 1, no. 2, 2012.

[30]

A.L. Nemmour, F. Mehazzem, A. Khezzar, and R. Abdessemed, "Advanced Backstepping controller for induction generator using multi-scalar machine model for wind power purposes", J. Renew. Energy, vol. 35, no. 10, pp. 2375-2380, 2010. [http://dx.doi.org/10.1016/j.renene.2010.02.016]

Improved Indirect Power Control of Wind Energy Conversion Systems, 2019, 9-25

9

CHAPTER 2

Overview of Wind Energy Conversion Systems (WECS) Abstract: The aim of this chapter is to present an overview of the state of technology and discuss some technology tendency in the Power Electronics (PE) used for Wind Power Applications (WPA). Firstly, technological and commercial developments in wind power generation are generally discussed. Next, the wind turbine concept is illustrated and explained using different types of generator. The control structure of wind-turbines (WTs) is explained using DFIG, Asynchronous and Synchronous Generator (ASG and SG). Finally, the last section focuses on a detailed literature review describing DFIG based wind turbine-generator systems in terms of modeling and control strategies.

Keywords: A wound rotor induction generator (WRIG), Asynchronous and Synchronous Generator (ASG and SG), Doubly Fed Induction Generator (DFIG), Wind Turbines (WTs), Wind Power Applications (WPAs). 1. WIND POWER DEVELOPMENT The increasing wind power capacity between 1999 and 2020 is illustrated in Fig. (2.1), and it can be shown that the wind power (WP) has developed fast to an ability of 283 GW with nearly 45 GW installed only in 2012, and this number is probable to reach 760 GW in 2020 on reasonable scenario [1 - 3]. WP raises more important than any other renewable energy and is becoming certainly a significant player in the recent energy supply system. For example, Denmark has a high diffusion by WP and today more than 30% of the electric power consumption is enclosed by wind. This state has even the desire to attain 100% non-fossil based power generation system by 2050 [4]. With regard to markets and constructors, the United States has become the largest market with an installed capacity of more than 13.1 GW in 2012, with China (13 GW) and the Europe Union (11.9 GW) sharing about 87% of the world market [4]. Fayssal Amrane & Azeddine Chaiba All rights reserved-© 2019 Bentham Science Publishers

10 Improved Indirect Power Control of Wind Energy Conversion Systems

Amrane and Azeddine

Giga Watts 900

792

800 700 600

Global cumulative wind power capacity 487 433 (GigaWatts) 370

500 400 300 200 100 0

159 94 121 74 59 48 24 31 39

283 198 238

318

…

20012002 2003200420052006 2007200820092010 2011201220132014 20152016

2020 (E)

Years

Fig. (2.1). Global increasing wind power capacity from 2001 to 2020 [1]. 10 MW D 190 m 7-8 MW D 164 m 5 MW D 124 m 2 MW D 80 m

50 KW D 15 m

100 KW D 20 m

1980 Rotational Speed

Power Electronics

500 KW D 40 m

1985

600 KW D 50 m

1990

Fixed Rating: Role:

2012

2020 (E)

Variable

Partially variable

10 % Soft Starter

2005

2000

1995

30 %

Rotor Rotor Resistance Power Control Control

100 % Full Generator Power Control

Fig. (2.2). Evolution of WT size and the power electronics seen from 1980 to 2020 (estimated). Orange circle: means the power coverage by power electronics, D: means diameter of the rotor [1].

Furthermore, to the fast progress in the full connected capacity, the size of single WT is also cumulative intensely to get a cheap price per generated kilowatt hour. The increasing tendencies of developing turbine dimension among 1980 and 2018 are shown in Fig. (2.2), where the development of PEs in the WTS is also shown.

Overview of Wind Energy

Improved Indirect Power Control of Wind Energy Conversion Systems 11

It is well-known that the cutting-edge 8-MW WTs based on a diameter of 164 m have before now shown up in 2012 [5]. At present greatest of the turbine producers are developing products in the power range 4.5–8 MW, and it is estimated that gradually great WTs even up to 10-MW will seem in 2018, will be existent in the following years [1]. 2. WIND TURBINE CONCEPTS The general structure of Wind Energy Conversion System (WECS) containing an aerodynamic and electro-mechanical mechanism which transforms wind kinetic energy to electrical energy as displayed in Fig. (2.3).

Wind

Electrical Aspect:

Mecanical Aspect:

Aerodynamic Aspect:

Wind turbinerotor

Gearbox

Wind turbineGenerator

Utility grid Power electronics converter

Fig. (2.3). Power conversion stages in a typical WTS.

Wind power generation (WPG) uses whichever variable or fixed speed turbines which can be characterized into four (04) main types. The principal difference between these wind turbines categories is the method which is used in order to make imperfect the aerodynamic efficiency of the rotor regardless of numerous wind speed conditions. So these 04 (four) categories are illustrated below [6]: 2.1. Fixed Speed Wind Turbines (WT Type A) Type “A” wind turbine (WT) is realized when an asynchronous squirrel-cage induction generator (SCIG) is associated directly to the network through a transformer. This type of WT desires an adjustment to prevent driving process during low wind speeds, and the consumption of reactive power present the main problem because there is no reactive power controller.

12 Improved Indirect Power Control of Wind Energy Conversion Systems

Amrane and Azeddine

2.2. Partial Variable Speed Wind Turbine (VS-WT) Using Variable Rotor Resistance (Type B) This type deals on a wound rotor induction generator (WRIG) be straight linked to the network. The measured resistances are associated in chain (series) with the rotor phase windings. In this manner, the global rotor resistances can be controlled, and consequently the output power and the slip can also be controlled. 2.3. VS-WT Using Partial Scale Power Converter (WT Type C) This procedure, acknowledged as the doubly-fed induction generator (DFIG) notion, uses a variable speed regulator WT. The DFIG’ stator phase windings are straight associated to the network, whereas the rotor is linked to a back-to-back converter via slip rings. A-Advantages of the DFIG [7] ●

●

● ●

The capacity of decoupling the reactive and active power by regulating the rotor terminal voltages. The DFIG is e in manufacture and economical than a permanent magnet synchronous generator (PMSG). Need a rigid network. The power converters is characteristically rated ±30% of the rated power, and this feature offers several advantages, for example, decreased converter cost, minimized filter cost and volume, fewer switching sufferers & harmonic injections into the network, and enhanced global efficiency [6].

B-Drawbacks of the DFIG [8 - 11] ● ● ●

Requires slip-rings and gearbox, which will need regular upkeep. Limitation for fault ride through (FRT) ability and requires protection schemes. Reactive power capability limitation and complex control schemes.

2.4. VS-WT using Full Scale Power Converter (Type D) This topology frequently uses a PMSG. The stator windings are associated to the network through a complete-scale power converter. This kind of WT adopts a gearless notion, instead of linking a gearbox to the generator, a driven generator is placed without a gearbox. The drawbacks of the main two categories of WTs are:

Overview of Wind Energy

1. 2. 3. 4.

Improved Indirect Power Control of Wind Energy Conversion Systems 13

Don’t support any speed regulation, Absence of reactive power compensation, Need a rigid network, Mechanical configuration must be capable to support great mechanical pressure produced by wind squalls.

Currently, DFIGs are most usually used in the WT manufacturing. In view of these advantages of the DFIG-based wind turbine-generator systems (WT-GS), this eBook will only concentrate on DFIGs and obviously in the next chapters; we will propose some detailed work about the mathematical models and control schemes. 3. CONTROL STRUCTURE OF WTS The control of WT includes mutually fast and slow control dynamics [1] and [12, 13], as illustrated in Fig. (2.5), where an overall control structure for a WTS, counting generator, turbine, converter and filter. The WT concept can both be the type shown in Fig. (2.4a and b). Usually, the power flow has to be managed prudently in or out side of the generation system. The generated power should be controlled using mechanical parts (e.g., pitch angle of blades). The full control system has to track the power production controls given by transmission system operator / distribution system operator. In the case of operation under grid fault, numerous subsystems in the WT which based on coordinated control such as, braking crowbar/chopper, grid/rotor side converters and pitch angle regulator are needed.  !"   " 
     


8

(

) 

(

6%

5


. !

 "/

+

(

(

      

  

5


6%

. !

  (



5


,# 7

. !

(

(  

$, 



 )




*

 




  

 "/

. !

(

(

*

5


,# 7




 

9

.,(      

  

 !"   $" - ," -     $,

(



Fig. (2.4). A: Variable-speed wind turbine with partial-scale power converter and a DFIG and B: Variablespeed wind turbine with full-scale power converter.

14 Improved Indirect Power Control of Wind Energy Conversion Systems

Amrane and Azeddine

(

) 

(

6%

5


. !

 "/



,# 7

5


(




1



. !

(

 

(

*

/




 




(



+
 

2 

1 ! ) !